In complex problem solving, such as medical diagnoses, the accuracy of initial hypothesis generally determines solution efficiency since it directs the collection and interpretation of evidence. Initial hypothesis generation represents a classification task in which a problem is categorization on the basis of a limited set of immediately apparent features. Current cognitive psychology theories suggests people categorize both by comparing new instances to category-summary information (prototype matching) and to specifically experienced class members (exemplar matching). Little is known, however, as to what determines which type of cognitive representation will be used as the basis for classification in a particular situation. This is important since reliance on different representations can produce different judgmental biases. Two studies are reported that employed a simulated medical diagnosis task to investigate how different training experiences influence subjects' cognitive representation of a simple disease classification system. Differences in the speed, accuracy, and certainty with which subject's classified new cases indicated that different training experiences lead them to rely on different cognitive representations in classifying new disease cases. Four studies are proposed to further investigate the impact of different training experiences on subjects' (a) flexibility in modifying an initial categorization when faced with new and contradictory information, (b) ability to learn the relative diagnosticity of different symptoms, (c) reliance on exemplar- and category-level information when both are available as part of their cognitive representations, and (d) ability to classify an illness at an appropriate level when confronted by a multi-level, hierarchical classification system. Results of the studies are seen to have implications for theories of cognition and problem solving as well for the design of effective programs to train clinical diagnosticians.